Abstract
Regional climate modeling using convection‐permitting models (CPMs; horizontal grid spacing <4 km) emerges as a promising framework to provide more reliable climate information on regional to local scales compared to traditionally used large‐scale models (LSMs; horizontal grid spacing >10 km). CPMs no longer rely on convection parameterization schemes, which had been identified as a major source of errors and uncertainties in LSMs. Moreover, CPMs allow for a more accurate representation of surface and orography fields. The drawback of CPMs is the high demand on computational resources. For this reason, first CPM climate simulations only appeared a decade ago. In this study, we aim to provide a common basis for CPM climate simulations by giving a holistic review of the topic. The most important components in CPMs such as physical parameterizations and dynamical formulations are discussed critically. An overview of weaknesses and an outlook on required future developments is provided. Most importantly, this review presents the consolidated outcome of studies that addressed the added value of CPM climate simulations compared to LSMs. Improvements are evident mostly for climate statistics related to deep convection, mountainous regions, or extreme events. The climate change signals of CPM simulations suggest an increase in flash floods, changes in hail storm characteristics, and reductions in the snowpack over mountains. In conclusion, CPMs are a very promising tool for future climate research. However, coordinated modeling programs are crucially needed to advance parameterizations of unresolved physics and to assess the full potential of CPMs.
Highlights
A fundamental challenge in climate science is the scale gap between climate information provided by climate models and the needs of impact researchers, stakeholders, and policy makers
We review the following: (1) What grid spacing is needed for convection-permitting model (CPM) climate simulations? (2) What is the best downscaling strategy to convection-permitting scales? (3) What are the most important model components that require further development? (4) What are, in theory, the added values of CPM climate simulations compared to large-scale model (LSM) simulations? (5) What added values could be demonstrated in practical applications? (6) And what can we learn from CPM about future climate change that is not assessable from LSM?
We present the rationale and quality of CPM climate simulations for modeling current climate, their added value and common differences compared to LSM simulations, and differences in their future climate projections compared to LSM
Summary
A fundamental challenge in climate science is the scale gap between climate information provided by climate models and the needs of impact researchers, stakeholders, and policy makers. This approach telescopically nests limited-area domains at decreasing horizontal grid spacings with boundary conditions provided by a GCM or reanalysis until convection-permitting scales are reached This approach was first used in numerical weather prediction, and numerous studies demonstrated the benefits of CPM climate simulations forecasts of severe weather [e.g., Bernardet et al, 2000; Done et al, 2004; Schwartz et al, 2009; Weusthoff et al, 2010] or for simulating rainfall intensity spectra [Davis et al, 2006]. To reduce the computational challenges of global CPMs, the third approach uses GCM with the so-called superparameterizations (Figure 1c) [Grabowski and Smolarkiewicz, 1999; Khairoutdinov and Randall, 2001] Within this framework, each GCM grid column embeds a two-dimensional cloud-resolving model. We review the following: (1) What grid spacing is needed for CPM climate simulations (section 3)? (2) What is the best downscaling strategy to convection-permitting scales (section 4)? (3) What are the most important model components that require further development (section 5)? (4) What are, in theory, the added values of CPM climate simulations compared to LSM simulations (section 6.1)? (5) What added values could be demonstrated in practical applications (section 6)? (6) And what can we learn from CPM about future climate change that is not assessable from LSM (section 7)?
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